Sharon Yixuan Li
University of Wisconsin–Madison — Computer Sciences · Assistant Professor
Research focus: out-of-distribution detection · trustworthy/reliable ML · open-world learning · deep learning safety
针对申请指南中提到的手动应用程序准备审计，请构建以 out-of-distribution detection、trustworthy/reliable ML、deep learning safety、open-world learning、Sharon Yixuan Li、LLM、rag、ai、li 为基准的拟合参数图，并能够灵活实现基于代理系统的可代理性量化。请提及一项近期发表的论文或项目，并说明您计划在第一个学期启动的具体扩展工作。
Who this advisor fits / 什么情况下适合你
- High-bar reliable-AI target; applicants should show exceptional fit and read the advising statement, then verify placement/current advising directly.
- 高门槛可保护性目标；申请机构应展示卓越契合度，并仔细阅读指导说明，随后直接核实当前指导与就业情况。
What to watch for / 什么情况下要慎重
- You need strong placement evidence, but public signals for this PI are still thin.
- 你需要强证据的毕业去向分布，而这位 PI 目前公开信号仍较薄。
Public evidence as of 2026-06-10
These are decision-support signals compiled from public evidence (faculty pages, publications, lab sites) to help you ask better questions — not a ranking, rating, or allegation about this advisor. / 以上为基于公开信息整理的择校参考，帮助你提出更好的问题，并非排名、评分或对该导师的指控。
Ask a verified 学长学姐 / 同校 .edu 认证点评
The thing applicants say only 师兄师姐 can tell you — current & former students of this lab, verified by their school .edu. Open the full dossier to read or add a verified note.